Knowledge Engineer (Data Interoperability / Data Modeling / Healthcare)

The perfect candidate:

The perfect candidate has a University Degree in Data Science / Engineering and at least 3 years of experience of working with data interoperability preferably in the pharmaceutical / medical device environment.

Also expertise in knowledge engineering, software engineering, data modeling, healthcare interoperability, data integration, semantic/graph technologies, data analytics and project management are expected.
We are looking for a motivated and self-driven individual who is ready to come on-site at least one time a week.

General Information:

• Start date: 01.09.2024 (ASAP or latet on 01.10.2024)
• Planned duration: 24 months with further extension planned and intended
• Workplace: Basel
• Workload: 100%
• Remote/Home Office: partial

Background:

The main goal of this project is about developing data technologies, algorithms, models and analytics to enable continuous discovery as well as assess economic value.

The contribution to Diagnostics centers on building and driving the implementation of reusable data products for use by Diagnostics as well as within customer facing software products; establish data architecture to link data products across Diagnostics and beyond; strengthening data skills and mindsets; providing Real World Data and information science expertise to Diagnostics as well as data & analytics across the company.

Tasks & Responsibilities:

• Collaborate with various product teams to shape the development and integration of data models and standardization into the product portfolio and enable FAIR (findable, accessible, interoperable, reusable) data services
• Collaborate with engineering and business teams and co-drive projects to implement interoperability standards for  devices and digital products adhering to FAIR principles
• Investigate innovative methods to generate new business insights from interlinked data sources (lab and clinical) that may mature into new features of digital products
• Drive the adoption and integration of interoperability standards including terminological resources (e.g. FHIR, HL7v2, LOINC, SNOMED) for RIS digital products
• Engage with internal key customers and stakeholders to understand their business needs, pain points using a customer-centric approach
• Co-create robust solutions starting out from prototypes 
• Drive automation of data and software services to achieve continuous delivery e.g. by setting up code repositories, automation pipelines, quality assurance, etc.

Must Haves:

• Work experience of minimum 3 years with data interoperability
• University Degree in Computer Science / Engineering related fields, preferably PhD degree (such as Software Engineering, Architecture, Data Science, Mathematics, Bioinformatics or similar areas of academic discipline)
• Strong software engineering skills and various programming languages such as Python, Java. Any knowledge of frontend programming languages such as Typescript, Angular, etc. is a plus. Any knowledge of data engineering and cloud skills is a plus
• Background in data interoperability technologies, such as data integration, data standards and terminologies (e.g. FHIR, HL7v2, SNOMED or LOINC)
• Good knowledge in (meta) data management approaches such as relational and graph databases
• Strong stakeholder management and collaboration skills
• Working independently in cross-functional and distributed teams
• Ability to work in changing, agile, multinational and multiple location environment
• Very good communication and presentation skills
• Fluency in English

Nice to have: 

• Experience in the pharmaceutical / medical device environment and in diagnostics is a plus